Publication - Formant Estimation of Speech Signals Using Subspace-Based Spectral Analysis

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Formant Estimation of Speech Signals Using Subspace-Based Spectral Analysis

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Type:  
In Proceedings

 

Year: 2006
Authors: Sotiris Karabetsos; Pirros Tsiakoulis; Stavroula-Evita Fotinea; Ioannis Dologlou
Book title: Proc. EUSIPCO 2006 (14th European Signal Processing Conference)
Address: Florence, Italy
Date: September 4-8
Abstract:
The objective of this paper is to propose a signal processing scheme that employs subspace-based spectral analysis for the purpose of formant estimation of speech signals. Specifically, the scheme is based on decimative Spectral estimation that uses Eigenanalysis and SVD (Singular Value Decomposition). The underlying model assumes a decomposition of the processed signal into complex damped sinusoids. In the case of formant tracking, the algorithm is applied on a small amount of the autocorrelation coefficients of a speech frame. The proposed scheme is evaluated on both artificial and real speech utterances from the TIMIT database. For the first case, comparative results to standard methods are provided which indicate that the proposed methodology successfully estimates formant trajectories.
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